AIMC Topic: Deep Learning

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Deep learning for sex classification in resting-state and task functional brain networks from the UK Biobank.

NeuroImage
Classification of whole-brain functional connectivity MRI data with convolutional neural networks (CNNs) has shown promise, but the complexity of these models impedes understanding of which aspects of brain activity contribute to classification. Whil...

DeepCervix: A deep learning-based framework for the classification of cervical cells using hybrid deep feature fusion techniques.

Computers in biology and medicine
Cervical cancer, one of the most common fatal cancers among women, can be prevented by regular screening to detect any precancerous lesions at early stages and treat them. Pap smear test is a widely performed screening technique for early detection o...

Deep learning approach to predict sentinel lymph node status directly from routine histology of primary melanoma tumours.

European journal of cancer (Oxford, England : 1990)
AIM: Sentinel lymph node status is a central prognostic factor for melanomas. However, the surgical excision involves some risks for affected patients. In this study, we therefore aimed to develop a digital biomarker that can predict lymph node metas...

Towards Lifespan Automation for Based on Deep Learning: Analysing Convolutional and Recurrent Neural Networks for Dead or Live Classification.

Sensors (Basel, Switzerland)
The automation of lifespan assays with in standard Petri dishes is a challenging problem because there are several problems hindering detection such as occlusions at the plate edges, dirt accumulation, and worm aggregations. Moreover, determining wh...

Learning Carbohydrate Digestion and Insulin Absorption Curves Using Blood Glucose Level Prediction and Deep Learning Models.

Sensors (Basel, Switzerland)
Type 1 diabetes is a chronic disease caused by the inability of the pancreas to produce insulin. Patients suffering type 1 diabetes depend on the appropriate estimation of the units of insulin they have to use in order to keep blood glucose levels in...

Deep-Learning-Based Multimodal Emotion Classification for Music Videos.

Sensors (Basel, Switzerland)
Music videos contain a great deal of visual and acoustic information. Each information source within a music video influences the emotions conveyed through the audio and video, suggesting that only a multimodal approach is capable of achieving effici...

The impact of site-specific digital histology signatures on deep learning model accuracy and bias.

Nature communications
The Cancer Genome Atlas (TCGA) is one of the largest biorepositories of digital histology. Deep learning (DL) models have been trained on TCGA to predict numerous features directly from histology, including survival, gene expression patterns, and dri...

Value of Rehabilitation Training for Children with Cerebral Palsy Diagnosed and Analyzed by Computed Tomography Imaging Information Features under Deep Learning.

Journal of healthcare engineering
To analyze the brain CT imaging data of children with cerebral palsy (CP), deep learning-based electronic computed tomography (CT) imaging information characteristics were used, thereby providing help for the rehabilitation analysis of children with ...

CT Image Analysis and Clinical Diagnosis of New Coronary Pneumonia Based on Improved Convolutional Neural Network.

Computational and mathematical methods in medicine
In this paper, based on the improved convolutional neural network, in-depth analysis of the CT image of the new coronary pneumonia, using the U-Net series of deep neural networks to semantically segment the CT image of the new coronary pneumonia, to ...

A Review of Intelligent Driving Pedestrian Detection Based on Deep Learning.

Computational intelligence and neuroscience
Pedestrian detection is a specific application of object detection. Compared with general object detection, it shows similarities and unique characteristics. In addition, it has important application value in the fields of intelligent driving and sec...